In general, advertisers want metrics that inform the advertisers about the effectiveness of a given advertising campaign. For example, advertisers may want to understand how a given advertising campaign affects user behavior, such as visiting a website, conducting a search for a product, and making a purchase to name a few. However, traditional test and control measures used to determine the effectiveness of advertising campaigns typically only look at the last exposure and do not account for frequency. In addition, these test and control measures do not handle a variety of impression types or overlapping of impressions. As a result, traditional test and control measures have difficulty in attributing relative credit to the impact of advertising given the different number of publishers and impression types found in today's marketplace.